Functional genomic tools for emerging model species
Authors: Erik Gudmunds, Christopher W. Wheat, Abderrahman Khila, Arild Husby
Journal: Trends in Ecology & Evolution (2022)

Understanding the molecular mechanisms underlying phenotypic evolution is a central goal in evolutionary biology.Unfortunately, causal associations between candidate loci and the phenotype are rarely established because the majority of associations are never validated with functional tools.We describe the latest developments in the use of functional tools, particularly RNAi and clustered regularly interspaced palindromic repeats (CRISPR)-Cas, to establish causal links between genotype and phenotype, and discuss some methodological challenges when applying these tools that are unique to emerging model organisms.Specifically, we highlight a significant issue in that current functional studies in ecology and evolutionary biology to date rarely recapitulate ecologically relevant variation, and we suggest that gene editing in emerging model species should make more use of the HDR pathway to obtain relevant functional insights and thereby a deeper understanding of the genetic basis of traits. Most studies in the field of ecology and evolution aiming to connect genotype to phenotype rarely validate identified loci using functional tools. Recent developments in RNA interference (RNAi) and clustered regularly interspaced palindromic repeats (CRISPR)-Cas genome editing have dramatically increased the feasibility of functional validation. However, these methods come with specific challenges when applied to emerging model organisms, including limited spatial control of gene silencing, low knock-in efficiencies, and low throughput of functional validation. Moreover, many functional studies to date do not recapitulate ecologically relevant variation, and this limits their scope for deeper insights into evolutionary processes. We therefore argue that increased use of gene editing by allelic replacement through homology-directed repair (HDR) would greatly benefit the field of ecology and evolution. Most studies in the field of ecology and evolution aiming to connect genotype to phenotype rarely validate identified loci using functional tools. Recent developments in RNA interference (RNAi) and clustered regularly interspaced palindromic repeats (CRISPR)-Cas genome editing have dramatically increased the feasibility of functional validation. However, these methods come with specific challenges when applied to emerging model organisms, including limited spatial control of gene silencing, low knock-in efficiencies, and low throughput of functional validation. Moreover, many functional studies to date do not recapitulate ecologically relevant variation, and this limits their scope for deeper insights into evolutionary processes. We therefore argue that increased use of gene editing by allelic replacement through homology-directed repair (HDR) would greatly benefit the field of ecology and evolution. A fundamental aim in ecology and evolution is to identify the genomic variation that underlies micro- and macroevolutionary dynamics [1.Vitti J.J. et al.Detecting natural selection in genomic data.Annu. Rev. Genet. 2013; 47: 97-120Crossref PubMed Scopus (397) Google Scholar]. In the present post-genomic era, diverse tools and datasets are routinely used for this purpose in emerging model organisms (see Glossary), ranging from genome-wide population data and various phenotype association approaches to differential expression analysis and chromatin accessibility assays [2.Jamann T.M. et al.QTL mapping using high-throughput sequencing.in: Alonso J.M. Stepanova A.N. Plant Functional Genomics: Methods and Protocols. Springer, 2015: 257-285Crossref Scopus (20) Google Scholar,3.van der Burg K.R.L. et al.Genomic architecture of a genetically assimilated seasonal color pattern.Science. 2020; 370: 721-725Crossref PubMed Scopus (24) Google Scholar]. Although such methods are advancing our understanding of genotype–phenotype relationships for traits involved in adaptation and speciation [3.van der Burg K.R.L. et al.Genomic architecture of a genetically assimilated seasonal color pattern.Science. 2020; 370: 721-725Crossref PubMed Scopus (24) Google Scholar,4.Pardo-Diaz C. et al.Towards the identification of the loci of adaptive evolution.Methods Ecol. Evol. 2015; 6: 445-464Crossref PubMed Scopus (93) Google Scholar], they also have clear limitations, the most obvious being that they lack the ability to establish rigorous causal inferences between phenotypes and candidate genes or loci. However, molecular tools for manipulating gene function, such as RNAi and clustered regularly interspaced palindromic repeats (CRISPR)–CRISPR-associated protein (Cas), in recent years have also made it possible to establish a causal link between candidate loci and phenotype in emerging model organisms. In this review we address the growing need for such causal inferences, and we discuss some of the practical aspects of functional validation in emerging model organisms and the future role of RNAi and CRISPR-Cas technologies in ecology and evolution, with a strong emphasis on the challenge and importance of establishing ecological relevance in functional validation. Rather than investing in functional validation, the accessibility of functional genomics hasinstead predominantly resulted in an increase in the sample sizes of individuals, populations, and species used in the quest to identify loci involved in adaptation and speciation. The result is an ever-increasing number of studies that, after identifying candidate loci (e.g., through molecular tests of selection, allele-frequency patterns, association mapping, linkage analysis, and transcriptomic studies), discuss at length the potential evolutionary implications. These methods all have inherent challenges (reviewed in [5.Schielzeth H. et al.Success and failure in replication of genotype–phenotype associations: How does replication help in understanding the genetic basis of phenotypic variation in outbred populations?.Mol. Ecol. Resour. 2018; 18: 739-754Crossref PubMed Scopus (19) Google Scholar, 6.Liu Y. et al.On the dependency of cellular protein levels on mRNA abundance.Cell. 2016; 165: 535-550Abstract Full Text Full Text PDF PubMed Scopus (1576) Google Scholar, 7.Schielzeth H. Husby A. Challenges and prospects in genome-wide quantitative trait loci mapping of standing genetic variation in natural populations.Ann. N. Y. Acad. Sci. 2014; 1320: 35-57Crossref PubMed Scopus (41) Google Scholar, 8.Wellenreuther M. Hansson B. Detecting polygenic evolution: problems, pitfalls, and promises.Trends Genet. TIG. 2016; 32: 155-164Abstract Full Text Full Text PDF PubMed Scopus (84) Google Scholar]), but common to them is the limitation that they do not establish causal associations between genotype and phenotype. Drawing rigorous conclusions from this body of evidence is therefore challenging, and interpretations of such insights should be considered carefully when attempting to understand the genotype–phenotype relationship. Given these circumstances, we raise two aspects worth considering when investigating the functional genetic basis of traits in ecology and evolution. First, although we acknowledge that the implementation of functional genetic methods is not possible or even desirable in some instances, we wish to stress that, in the absence of proper data allowing causal inferences, the field would greatly benefit from avoiding the use of causal language. Imprecise language degrades the importance of causal insights, impedes our understanding of how the natural world works, and bloats the field with false positive results [9.Siddiq M.A. et al.Experimental test and refutation of a classic case of molecular adaptation in Drosophila melanogaster.Nat. Ecol. Evol. 2017; 1: 25Crossref PubMed Scopus (21) Google Scholar]. Second, relying upon existing annotations without validation perpetuates bias. Consider a common hypothetical scenario, wherein candidate loci are identified using the intersection of gene expression data and SNP association mapping for a trait, where variants associated with the phenotype are in or near the coding sequences of several differentially expressed genes. The resulting candidate gene list is assessed, and hypotheses formed based on gene or sequence element annotations, which in turn are overwhelmingly based on genetic and molecular studies in the closest model organism (e.g., Drosophila melanogaster for insects, the mouse Mus musculus for mammals, the zebrafish Danio rerio for fish, Saccharomyces cerevisiae for yeast, Arabidopsis thaliana for plants, and so on). We note the duality of this approach: although this seems a sound way forward because many homologous genes share functions over deep evolutionary time, and this approach is necessary because no other such insights are possible, it also comes with a risk of erroneous inferences. Model organisms not only have many important genes of unknown function [10.Wu M. et al.CRISPR/Cas9 mediated genetic resource for unknown kinase and phosphatase genes in Drosophila.Sci. Rep. 2020; 10: 7383Crossref PubMed Scopus (3) Google Scholar] but functions also certainly change over time for orthologous genes [11.Verster A.J. et al.Comparative RNAi screens in C. elegans and C. briggsae reveal the impact of developmental system drift on gene function.PLoS Genet. 2014; 10e1004077Crossref PubMed Scopus (41) Google Scholar]. Thus, relying solely on functional annotation from other organisms can restrict the ability to detect lineage-specific protein functions or genes, moonlighting proteins, or cases of gene co-option that have evolved to shape the phenotype of interest, especially because subsequent changes to functional annotations can even alter the biological conclusions [12.Tomczak A. et al.Interpretation of biological experiments changes with evolution of the Gene Ontology and its annotations.Sci. Rep. 2018; 8: 5115Crossref PubMed Scopus (66) Google Scholar]. Equally problematic, relying upon functional annotations for selecting candidate genes generates ascertainment bias because genes without assigned functions are almost always avoided, even though species-specific genes can clearly be important [11.Verster A.J. et al.Comparative RNAi screens in C. elegans and C. briggsae reveal the impact of developmental system drift on gene function.PLoS Genet. 2014; 10e1004077Crossref PubMed Scopus (41) Google Scholar]. The magnitude of this problem is huge and the ramifications vast – even in Homo sapiens <10% of genes have been the focus of >90% of published papers [13.Stoeger T. et al.Large-scale investigation of the reasons why potentially important genes are ignored.PLoS Biol. 2018; 16e2006643Crossref Scopus (125) Google Scholar]. We highlight this annotation bias, as well as the aforementioned issues, to demonstrate not only the importance but also the empowerment of being able to functionally test candidate genes irrespective of whether they have or lack annotations. A recent study by van der Burg et al. [3.van der Burg K.R.L. et al.Genomic architecture of a genetically assimilated seasonal color pattern.Science. 2020; 370: 721-725Crossref PubMed Scopus (24) Google Scholar] exemplifies all of these issues with elegance, wherein the authors investigated the genetic assimilation of plasticity in butterfly wing coloration, arriving at 13 candidate loci after intersecting genome-wide association study (GWAS) and RNA-seq time-series results. They then used CRISPR-Cas to manipulate four of these candidate genes. Knockout (KO) of their first choice, a locus annotated to butterfly wing-pattern function (cortex), predictably affected wing color. Of the two other annotated genes, one had no phenotypic effect (Dscam3) whereas the other did (trehalase). Finally, KO of the then uncharacterized and unannotated gene demonstrated it to be causally involved in wing coloration plasticity, and it was named herfst. Had the authors chosen to only KO cortex, two novel loci would have been missed, one of which (the central metabolic gene trehalase) has an unpredicted role in wing patterning. Had they not conducted functional validation, the role of the neuronal developmental gene Dscam3 in wing patterning might have generated a line of inquiry that in fact lacks causal support, and the novel role of trehalase might possibly have been discounted. Finally, their discovery of herfst not only provides important knowledge for future studies but also allows reanalysis of previous work. With more validation of components of studies in ecology and evolution, these types of functional insights will synergistically improve future association studies across a broader taxonomical range for phenotypes of interest to our field. Establishing functional tools for an emerging model system is by necessity a stepwise process that requires determination and effort. Although some species will never be amenable to functional manipulation, validation in others might be accomplished on the scale of months, which has led to an impressive proliferation of insightful studies using gene knockdown or KO techniques to explore the genetic basis of traits from candidates that were or had previously been identified from association-based approaches [14.Klaassen H. et al.CRISPR mutagenesis confirms the role of oca2 in melanin pigmentation in Astyanax mexicanus.Dev. 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These include phenomena such as the genetic basis of migration [21.Zhan S. et al.The genetics of monarch butterfly migration and warning colouration.Nature. 2014; 514: 317-321Crossref PubMed Scopus (186) Google Scholar], trait exaggeration [22.Toubiana W. Khila A. Fluctuating selection strength and intense male competition underlie variation and exaggeration of a water strider's male weapon.Proc. Biol. Sci. 2019; 28620182400PubMed Google Scholar], evolutionary innovations [23.Wagner G.P. Lynch V.J. Evolutionary novelties.Curr. Biol. 2010; 20: R48-R52Abstract Full Text Full Text PDF PubMed Scopus (184) Google Scholar], and polyphenisms [24.Casasa S. et al.Nutrition-responsive gene expression and the developmental evolution of insect polyphenism.Nat. Ecol. Evol. 2020; 4: 970-978Crossref PubMed Scopus (17) Google Scholar], to name but a few. RNAi is a molecular technique that is used to artificially downregulate the expression of a gene of interest to assess its functional importance at the phenotypic level. The downregulation of the gene occurs temporarily and is usually referred to as a gene knockdown because it reduces rather than eliminates protein production, as opposed to a gene KO. The use of RNAi largely relies on proteins of the endogenous small RNA pathways (e.g., microRNA, small interfering RNA, Piwi-interacting RNA) that are present in almost all eukaryotic lineages [25.Shabalina S.A. Koonin E.V. Origins and evolution of eukaryotic RNA interference.Trends Ecol. Evol. 2008; 23: 578-587Abstract Full Text Full Text PDF PubMed Scopus (364) Google Scholar]. Although the functions and dynamics of endogenous small RNA pathways across taxa are highly divergent and complex [26.Chapman E.J. Carrington J.C. Specialization and evolution of endogenous small RNA pathways.Nat. Rev. Genet. 2007; 8: 884-896Crossref PubMed Scopus (557) Google Scholar], exogenously induced RNAi is usually considered to follow a simplified conserved mechanism (Box 1) which makes RNAi a possibility for most eukaryotic emerging model organisms (although there are notable exceptions; e.g., Lepidoptera [27.Terenius O. et al.RNA interference in Lepidoptera: an overview of successful and unsuccessful studies and implications for experimental design.J. Insect Physiol. 2012; 57: 231-245Crossref Scopus (639) Google Scholar]).Box 1The nature of the RNAi pathway and how it enables sequence-specific knockdownsThe RNAi pathway was first discovered in plants and Caenorhabditis elegans [78.Fire A. et al.Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans.Nature. 1998; 391: 806-811Crossref PubMed Scopus (12060) Google Scholar,79.Hamilton A.J. Baulcombe D.C. A species of small antisense RNA in posttranscriptional gene silencing in plants.Science. 1999; 286: 950-952Crossref PubMed Scopus (2373) Google Scholar], where researchers observed a sequence-specific reduction of gene expression when they introduced double-stranded RNA (dsRNA) or antisense RNA (asRNA) into cells or whole organisms. Research in different model systems has since elucidated the molecular mechanisms of RNAi [80.Wilson R.C. Doudna J.A. Molecular mechanisms of RNA interference.Annu. Rev. Biophys. 2013; 42: 217-239Crossref PubMed Scopus (732) Google Scholar]. The core pathway is initiated by cleavage of dsRNA by the endonuclease Dicer into smaller 20–25 nt fragments [81.Bernstein E. et al.Role for a bidentate ribonuclease in the initiation step of RNA interference.Nature. 2001; 409: 363-366Crossref PubMed Scopus (3854) Google Scholar]. From these small RNA fragments, RNA strands associate with proteins of the Argonaut family and, together with additional factors, form the RNA-induced silencing complex (RISC) [82.Hammond S.M. et al.An RNA-directed nuclease mediates post-transcriptional gene silencing in Drosophila cells.Nature. 2000; 404: 293-296Crossref PubMed Scopus (2443) Google Scholar]. Based on the sequence of the small RNA, the RISC recognizes and binds to other RNA molecules and interferes with their expression by direct endonucleolytic cleavage, translational repression, or by directing the formation of heterochromatin at the corresponding genomic locus [45.Podolska K. Svoboda P. Targeting genes in living mammals by RNA interference.Brief. Funct. Genomics. 2011; 10: 238-247Crossref PubMed Scopus (12) Google Scholar].The use of RNAi is dependent on the ability of the organism to transport RNA into the cytosol where the mechanisms described above are initiated. In some groups the transport of dsRNA is highly efficient, whereas in other groups such as vertebrates, dsRNA transport across cell membranes does not occur easily. In such cases, dsRNA introduction can be aided by exogenous transport agents or methods including viral vectors and electroporation, or delivering the dsRNA with the use of vehicle molecules such as cationic lipids [45.Podolska K. Svoboda P. Targeting genes in living mammals by RNA interference.Brief. Funct. Genomics. 2011; 10: 238-247Crossref PubMed Scopus (12) Google Scholar]. A common technique for dsRNA introduction into emerging model organisms is microinjection, where the dsRNA in solution is injected directly into the tissue. This method is dependent on whether the organism has an efficient endogenous system for dsRNA transport, and is usually referred to as systemic RNAi. The strategy of delivering dsRNA into the relevant emerging model organism can, to a large extent, be guided by the methods applied in the nearest model organism. The RNAi pathway was first discovered in plants and Caenorhabditis elegans [78.Fire A. et al.Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans.Nature. 1998; 391: 806-811Crossref PubMed Scopus (12060) Google Scholar,79.Hamilton A.J. Baulcombe D.C. A species of small antisense RNA in posttranscriptional gene silencing in plants.Science. 1999; 286: 950-952Crossref PubMed Scopus (2373) Google Scholar], where researchers observed a sequence-specific reduction of gene expression when they introduced double-stranded RNA (dsRNA) or antisense RNA (asRNA) into cells or whole organisms. Research in different model systems has since elucidated the molecular mechanisms of RNAi [80.Wilson R.C. Doudna J.A. Molecular mechanisms of RNA interference.Annu. Rev. Biophys. 2013; 42: 217-239Crossref PubMed Scopus (732) Google Scholar]. The core pathway is initiated by cleavage of dsRNA by the endonuclease Dicer into smaller 20–25 nt fragments [81.Bernstein E. et al.Role for a bidentate ribonuclease in the initiation step of RNA interference.Nature. 2001; 409: 363-366Crossref PubMed Scopus (3854) Google Scholar]. From these small RNA fragments, RNA strands associate with proteins of the Argonaut family and, together with additional factors, form the RNA-induced silencing complex (RISC) [82.Hammond S.M. et al.An RNA-directed nuclease mediates post-transcriptional gene silencing in Drosophila cells.Nature. 2000; 404: 293-296Crossref PubMed Scopus (2443) Google Scholar]. Based on the sequence of the small RNA, the RISC recognizes and binds to other RNA molecules and interferes with their expression by direct endonucleolytic cleavage, translational repression, or by directing the formation of heterochromatin at the corresponding genomic locus [45.Podolska K. Svoboda P. Targeting genes in living mammals by RNA interference.Brief. Funct. Genomics. 2011; 10: 238-247Crossref PubMed Scopus (12) Google Scholar]. The use of RNAi is dependent on the ability of the organism to transport RNA into the cytosol where the mechanisms described above are initiated. In some groups the transport of dsRNA is highly efficient, whereas in other groups such as vertebrates, dsRNA transport across cell membranes does not occur easily. In such cases, dsRNA introduction can be aided by exogenous transport agents or methods including viral vectors and electroporation, or delivering the dsRNA with the use of vehicle molecules such as cationic lipids [45.Podolska K. Svoboda P. Targeting genes in living mammals by RNA interference.Brief. Funct. Genomics. 2011; 10: 238-247Crossref PubMed Scopus (12) Google Scholar]. A common technique for dsRNA introduction into emerging model organisms is microinjection, where the dsRNA in solution is injected directly into the tissue. This method is dependent on whether the organism has an efficient endogenous system for dsRNA transport, and is usually referred to as systemic RNAi. The strategy of delivering dsRNA into the relevant emerging model organism can, to a large extent, be guided by the methods applied in the nearest model organism. Apart from the generally broad applicability of RNAi in diverse taxa, additional advantages include initiation at specific developmental stages and the potential for tissue localization, both of which can minimize negative pleiotropic effects. Further, RNAi can be tuned by controlling the double-stranded RNA (dsRNA) dose to levels where the gene expression is not completely ablated [28.Killiny N. et al.Double-stranded RNA uptake through topical application, mediates silencing of five CYP4 genes and suppresses insecticide resistance in Diaphorina citri.PLoS One. 2014; 9e110536Crossref Scopus (116) Google Scholar,29.Refki P.N. et al.Emergence of tissue sensitivity to Hox protein levels underlies the evolution of an adaptive morphological trait.Dev. Biol. 2014; 392: 441-453Crossref PubMed Scopus (27) Google Scholar], thus enabling survival and phenotyping so as to infer function. For example, the function of an insulin receptor in insect wing polyphenism has been revealed by RNAi [30.Xu H.J. et al.Two insulin receptors determine alternative wing morphs in planthoppers.Nature. 2015; 519: 464-467Crossref PubMed Scopus (308) Google Scholar], whereas KO alleles cause embryonic lethality in the homozygous state [31.Zhao Y. et al.Mutations in NlInR1 affect normal growth and lifespan in the brown planthopper Nilaparvata lugens.Insect Biochem. Mol. Biol. 2019; 115103246Crossref PubMed Scopus (20) Google Scholar]. Finally, RNAi has also been used in several emerging model organisms to study polyphenisms [32.Zhang C.-X. et al.Molecular mechanisms of wing polymorphism in insects.Annu. Rev. Entomol. 2019; 64: 297-314Crossref PubMed Scopus (64) Google Scholar] which have rarely been studied in classical model organisms. Although large-scale RNAi screens for gene function are normally associated with classical model organisms [33.Liu Y. et al.Whole-animal genome-wide RNAi screen identifies networks regulating male germline stem cells in Drosophila.Nat. Commun. 2016; 7: 12149Crossref PubMed Scopus (17) Google Scholar,34.Wang G. et al.RNAi expression tuning, microfluidic screening, and genome recombineering for improved protein production in Saccharomyces cerevisiae.Proc. Natl. Acad. Sci. U. S. A. 2019; 116: 9324-9332Crossref PubMed Scopus (37) Google Scholar], screens of tens of genes are possible in emerging model organisms [35.Toubiana W. et al.The growth factor BMP11 is required for the development and evolution of a male exaggerated weapon and its associated fighting behavior in a water strider.PLoS Biol. 2021; 19e3001157Crossref PubMed Scopus (6) Google Scholar]. Efficient screens rely on overcoming the hurdle of dsRNA introduction into the organism, which in most cases is done through time-consuming microinjections, but targeting a modest set of genes (less than ~50) is achievable through microinjection techniques [17.Santos M.E. et al.Taxon-restricted genes at the origin of a novel trait allowing access to a new environment.Science. 2017; 358: 386-390Crossref PubMed Scopus (56) Google Scholar,35.Toubiana W. et al.The growth factor BMP11 is required for the development and evolution of a male exaggerated weapon and its associated fighting behavior in a water strider.PLoS Biol. 2021; 19e3001157Crossref PubMed Scopus (6) Google Scholar]. Some emerging model organisms are amenable to feeding RNAi [36.Feng D. et al.RNA Interference by ingested dsRNA-expressing bacteria to study shell biosynthesis and pigmentation in Crassostrea gigas.Mar. Biotechnol. 2019; 21: 526-536Crossref PubMed Scopus (23) Google Scholar,37.Whyard S. et al.Ingested double-stranded RNAs can act as species-specific insecticides.Insect Biochem. Mol. Biol. 2009; 39: 824-832Crossref PubMed Scopus (456) Google Scholar], which enables time-efficient knockdowns of many genes [38.Forsthoefel D.J. et al.An RNAi screen reveals intestinal regulators of branching morphogenesis, differentiation, and stem cell proliferation in planarians.Dev. Cell. 2012; 23: 691-704Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar]. In addition to feeding RNAi, topical application of dsRNA in insects [39.Wang Y. et al.Second-generation sequencing supply an effective way to screen RNAi targets in large scale for potential application in pest insect control.PLoS One. 2011; 6e18644Google Scholar] is an underutilized strategy for RNAi screens. One potential obstacle with RNAi is the efficiency with which dsRNA delivery and transport occurs within a treated individual because this varies across species [27.Terenius O. et al.RNA interference in Lepidoptera: an overview of successful and unsuccessful studies and implications for experimental design.J. Insect Physiol. 2012; 57: 231-245Crossref Scopus (639) Google Scholar] and even populations [40.Vogel E. et al.RNA interference in insects: protecting beneficials and controlling pests.Front. Physiol. 2019; 9: 1912Crossref PubMed Scopus (107) Google Scholar], generating variation that necessitates larger sample sizes. Another drawback is that, in organisms lacking systemic RNAi, administration of dsRNA for efficient knockdown is difficult. One strategy in vertebrates is to resort to delivery via viral vectors [41.Schepers U. RNA Interference in Practice: Principles, Basics, and Methods for Gene Silencing in C. elegans, Drosophila, and Mammals. John Wiley & Sons,